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Chinese control Conference

作者： JunLei Song MeiJuan Chen Chang Jiang YanXia Huang Qi Liu Yuan Meng WenQin Mo KaiFeng Dong Fang Jin China University of Geosciences Wuhan Hubei CN School of Automation China University of Geosciences Wuhan P. R. China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China

In the process of image acquisition and transmission, the image always generates noise due to internal and external interference. Noise reduces the quality of the image, and makes it difficult for subsequent image processing. Therefore, image denoising is very important in image processing. Wavelet denoising can effectively filter out noise and retain high-frequency information of the image, this method has the characteristics of fast operation speed and has become an important branch of image denoising. Threshold functions commonly used in wavelet threshold denoising include hard threshold function and soft threshold function. The hard threshold function is not continuous as a whole. Although the soft threshold function has good continuity, there is always a constant deviation between the processed coefficient and the original coefficient when the wavelet coefficient is large. In response to these deficiencies, this paper establishes a new improved threshold function based on traditional soft and hard threshold functions. By processing the thresholds of wavelet coefficients, a reasonable balance between smoothing and edge oscillations can be achieved after image denoising. The improved threshold function not only overcomes the shortcomings of the soft and hard threshold functions, but also provides more flexibility in the processing of image noise. Through MATLAB simulation, the denoising effects of the soft, hard threshold functions and the threshold function constructed in this paper are compared in terms of signal-to-noise ratio (SNR) and root mean square error (MSE). The MATLAB simulation results show that compared with the traditional threshold function, the improved threshold function has a higher signal-to-noise ratio (SNR = 26.27709) and a smaller mean square error (MSE = 153.4579), and it has a good noise reduction effect.

关键词： Wavelet coefficients Noise reduction Image denoising Correlation Signal to noise ratio

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Development of A Customizable Real-time Monitoring System for Networked control systems

Development of A Customizable Real-time Monitoring System fo...

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Chinese control Conference

作者： Haoran Tan Zhiwu Huang Min Wu School of Information Science and Engineering Central South University Changsha P. R. China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems Wuhan P. R. China

The design and implementation of a monitoring system for networked control systems (NCSs) are introduced in this paper. The monitoring system is developed in the .NET framework using C# according to the C/S architecture which allows the user to monitor network nodes without geographical limitations. The widgets used to display come from the National Instruments (NI) suit and are integrated in the system by reconstructing it. The user is able to design a monitoring interface freely by creating and customizing widgets dynamically. During the monitoring, the display value of the widget is synchronized with parameters and signals of NCSs through receiving data asynchronously from network notes. In particular, all elements of the matrix widely used in NCSs are supported for monitoring. The functionality and feasibility of the designed monitoring system are demonstrated via a networked control experiment. In addition, the saved data can be used in data driven control and model identification.

关键词： Monitoring Graphical user interfaces control systems Communication channels Mice Protocols Real-time systems

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Qualitative Elemental Analysis of Minerals Based on Energy Dispersive X - ray Fluorescence Spectrometry

Qualitative Elemental Analysis of Minerals Based on Energy D...

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Chinese control Conference (CCC)

作者： JunLei Song ZhiHeng Yang Jing Cai XiaoYong Ni DianHong Wang Xing Jin WenQin Mo KaiFeng Dong Fang Jin Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China School of Mechanical and Electronic Information china University of Geosciences Wuhan P. R. China

The research of miniaturized XRF/XRD analyzers are carried out in this paper, especially the qualitative analysis based on EDXRF, a miniaturized energy dispersive X-ray fluorescence spectrometry platform is designed and a qualitative elemental analysis software based on Android operating system is developed. The elemental qualitative analysis software can preprocess the X-ray feature spectrum by background eliminationsmoothing and energy coefficient calibration, after these pretreatments, the main elements of the sample can be analyzed. The experimental results show that the qualitative elemental analysis platform proposed in this paper can measure the elements of Al to Au in the periodic table, besides, the detection accuracy of multiple samples is higher than 97%. The mineral qualitative elemental analysis software proposed in this paper can be applied to any portable analysis platform based on Android operating system, moreover, it will spur advances in the development of the miniaturization and intelligent X-ray fluorescence spectrometer.

关键词： Minerals Software Calibration Spectroscopy Instruments Detectors Smoothing methods

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Stochastic stabilization of linear systems under delayed and noisy feedback control 36

Stochastic stabilization of linear systems under delayed and...

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第36届中国控制会议

作者： ZONG Xiaofeng LI Tao ZHANG Ji-Feng School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Shanghai Key Laboratory of Pure Mathematics and Mathematical Practice Department of MathematicsEast China Normal University Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences

ISBN: (纸本)9781538629185

This paper is to study the stabilizability and stabilization issues of linear dynamical systems based on the delayed and noisy feedback control. For the general linear systems, the necessary conditions and sufficient conditions for mean square and almost sure stabilizability are deduced and the corresponding feedback controls are designed according to the generalized algebraic Riccati equation. It is revealed that the stabilizability is up to the system parameters（delays, noises, and unstable eigenvalues of the original system） and unstable systems can be stabilized in mean square if the feedback control is disturbed by noises with small intensities. It is showed that second-order integrator systems must be stabilizable for any given noise intensity and delay.

关键词： Stabilization Feedback control Noise Delay

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Parallel medical imaging for intelligent medical image analysis: Concepts, methods, and applications

arXiv

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arXiv 2019年

作者： Gou, Chao Shen, Tianyu Zheng, Wenbo Xue, Huadan Yu, Hui Ji, Qiang Jin, Zhengyu Wang, Fei-Yue School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou510275 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Department of Radiology Peking Union Medical College Hospital Chinese Academy of Medical Sciences Peking Union Medical College Beijing100730 China School of Creative Technologies University of Portsmouth PortsmouthPO1 2DJ United Kingdom Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Qingdao Academy of Intelligent Industries Qingdao266000 China

Data-driven artificial intelligence technologies have made much progress in medical image analysis in the last decades. However, it still remains challenging due to its distinctive complexity of acquiring and annotating image data, extracting medical domain knowledge, and explaining the diagnostic decision for medical image analysis. In this paper, we propose a data-knowledge-driven framework termed as Parallel Medical Imaging (PMI) for intelligent medical image analysis based on the methodology of interactive ACP-based parallel intelligence. In the PMI framework, computational experiments with predictive learning in a data-driven way are conducted to extract medical knowledge for diagnostic decision support. Artificial imaging systems are introduced to select and prescriptively generate medical image data in a knowledge-driven way to utilize medical domain knowledge. Through the closed-loop optimization based on parallel execution, our proposed PMI framework can boost the generalization ability and alleviate the limitation of medical interpretation for diagnostic decisions. Furthermore, we illustrate the preliminary implementation of PMI method through the case studies of mammogram analysis and skin lesion image analysis. Experimental results on several public medical image datasets demonstrate the effectiveness of proposed PMI. © 2019, CC BY.

关键词： Medical imaging

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Relation Model of Burden Operation and State Variables of Blast Furnace Based on Low Frequency Feature Extraction*

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IFAC-PapersOnLine 2017年第1期50卷 13796-13801页

作者： Zhang, Kexin Wu, Min An, Jianqi Cao, Weihua Liu, Zhentao Ning, Fulong School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Faculty of Engineering China University of Geosciences wuhan430074 China Department of Computer Science School of Computing Tokyo Institute of Technology Yokohama226-8502 Japan

In the blast furnace ironmaking process, the running state of the blast furnace can be directly adjusted by the burden operation. Therefore, the explicit relation between the burden operation and the running state variables is vital for the blast furnace operators. However, the state variables of the blast furnace are affected by many factors and the burden matrix is complicated. In this paper, a support vector regression(SVR) predicting model based on low frequency feature extraction is proposed to solve these problems. First, the low frequency components of state variables time series which are mostly affected by the burden operation are extracted. Then, the dimensions of the burden matrix are reduced by a devised simple expression method. Finally, the relation model based on SVR is proposed to predict the values of the expected state variables according to the simplified burden matrix and the value of initial state variables. The simulation on real factory data indicates that the model reflects the accurate quantitative relation between the burden operation and the state variables. © 2017

关键词： Blast furnaces Blast furnace practice Extraction Feature extraction Support vector regression Blast furnace iron making Blast furnace operators burden operation Initial state variables Low frequency components Relation models State variables Support vector regression (SVR)

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A full-dq based adaptive virtual impedance compensation in virtual power frame for droop-controlled parallel inverters under unbalanced conditions

A full-dq based adaptive virtual impedance compensation in v...

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Annual Conference of Industrial Electronics Society

作者： Yuan Cao Zhen Li Zelun Lu Zhen Chen Xiangdong Liu School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing China

Distributed generation (DG) is connected through three-phase inverter to the microgrid. The virtual power based droop control can guarantee the pure decoupling between active and reactive power irrespective of low-voltage or high-voltage microgrid application if the line-impedance information is known in advance. However, unbalances are commonly existent in practice so that this conventional control fails in application due to the significant coupling between active and reactive power. To overcome this problem and further extend virtual power based method into unbalanced conditions, this paper proposes an improved virtual power decoupling technique using full-dq transformation, which is utilized to identify arbitrary unbalanced components under unbalanced conditions. The identified unbalances are further compensated as an virtual impedance so as to ensure the pure decoupling of active and reactive power in the virtual power frame. Finally, simulation results are provided to verify the effectiveness of the proposed method under unbalanced conditions.

关键词： Impedance Reactive power Inverters Microgrids Voltage control Frequency control Couplings

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Joint task management of sensor and weapon based on distributed management system

Joint task management of sensor and weapon based on distribu...

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Chinese control Conference (CCC)

作者： Zhang Mingyang Chen Chen Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing School of Automation Beijing Institute of Technology Beijing

ISBN: (纸本)9781538629185

In the modern war, many combat units combat collectively has become the main form. In the task management of the combat units, the calculation is large and the real-time requirement is high. To solve the problem better, a joint task management method of sensor and weapon based on distributed management system is proposed. Firstly, the distributed management system is constructed according to the target trajectory and the distribution of combat units. In the system, all the combat units are divided into several combinations, which only consist of a few combat units. As a result, the problem scale is reduced, and the real-time requirement of battlefield is met. Secondly, joint task management model of sensor and weapon is established. We consider time constraints and resource constraints to ensure the feasibility of the attack scheme, and consider the impact between sensor and weapon to achieve better combat effect. A discrete particle swarm optimization algorithm based on crossover strategy (CDPSO) is proposed to solve the model. The results show that the performance of the proposed algorithm is satisfactory in joint task management of sensor and weapon.

关键词： Weapons Distributed management Command and control systems Time factors Mathematical model Data processing Real-time systems

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ADP-Based Model Reference Adaptive control Design for Unknown Discrete-Time Nonlinear systems

ADP-Based Model Reference Adaptive Control Design for Unknow...

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Chinese control Conference (CCC)

作者： Wei Wang Xin Chen Fang Wang Hao Fu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China School of Electrical and Information Engineering Zhengzhou University of Light Industry Wuhan P. R. China

In engineering applications, it is very useful to make a nonlinear system behave like a linear stable system. However, how to design a model reference adaptive control (MRAC) as the nonlinear dynamics is unknown is the key problem. In this study, an MRAC with adaptive dynamic programming (ADP) algorithm is presented for discrete-time nonlinear unknown dynamic systems, in which a multi-layer neural network (NN) model is utilized to describe the nonlinear system's dynamics. Then based on this approximate model, a feedforward neuro-controller is developed as the desired control corresponding to the reference input. Third, the iterative ADP algorithm, in the form of actor-critic framework, employs two NNs to estimate the action value function, and generates the feedback control which, together with the feedforward neuro-controller, makes the state of the system track the reference model. Finally the feasibility of the new approach is verified by two numerical experiments.

关键词： Artificial neural networks Nonlinear systems Feedforward systems Optimal control Adaptation models Feedback control Mathematical model

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The 3D point clouds registration for human foot 3rd

The 3D point clouds registration for human foot

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3rd International Conference on Intelligence Science, ICIS 2018

作者： Xie, Yi Shang, Xiuqin Li, Yuqing Liu, Xiwei Zhu, Fenghua Xiong, Gang Pirttikangas, Susanna Zhou, Jiehan School of Electrical and Electronic Engineering The University of Manchester ManchesterM13 9PL United Kingdom The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Cloud Computing Center Chinese Academy of Sciences DongguanGuangdong China College of Information Science and Technology Beijing University of Chemical Technology Beijing China Qingdao Academy of Intelligent Industries Qingdao China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing100190 China The Center for Ubiquitous Computing University of Oulu Oulu Finland

ISBN: (纸本)9783030013127

For personalized design it is important to be able to collect, measure and evaluate individual properties of human beings. This paper proposes registration for the point clouds during foot 3D scanning. In the experiment, we get the point clouds of the human foot from the Artec 3D scanner and complete the registration of the point clouds from different visual angles. Dealing with the customized footwear, we choose a novel algorithm, which combines the NARF key point detector and the FPFH descriptor, to improve the efficiency of the initial iteration and reduce the computation burden of matching process. © IFIP International Federation for Information Processing 2018.

关键词： Iterative methods

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